development of optimal migration plan for new …the simple multi-attribute rating technique...
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DEVELOPMENT OF OPTIMAL MIGRATION
PLAN FOR NEW TRAFFIC SIGNAL
CONTROLLERS USING GIS AND MULTI-
CRITERIA DECISION MAKING
SURENDER GANTA
Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University in
partial fulfillment of the requirements for the degree of
Master of Science
In
Civil Engineering
Montasir M Abbas, Chair
Gerardo W Flintsch
Kathleen Hancock
July 01, 2010
Blacksburg
Keywords – Traffic Signal Controllers, Migration Plan, GIS, Multi-Criteria Decision Making
DEVELOPMENT OF OPTIMAL MIGRATION
PLAN FOR NEW TRAFFIC SIGNAL
CONTROLLERS USING GIS AND MULTI-
CRITERIA DECISION MAKING
SURENDER GANTA
ABSTRACT Signal Replacement decisions are often made based on the experience of the Traffic Engineers.
These decisions are made while considering the deployment time of the system, the new
technology available, and the performance of the system in the given location. However, there is
no set of proper guidelines or methods which can quantify the system replacement decision in
large scale projects. This thesis presents a methodology that can be applied to determine optimal
migration plans for traffic signal controllers. A Multi-Criteria Decision Making technique has
been adopted to evaluate various traffic signal controllers. Various controller manuals were
studied and information was obtained from the vendors of the controllers. In addition to that,
Geographic Information System (GIS) has been used as a tool to evaluate and identify the areas
where the traffic signal controllers have to be replaced first. The study considers the budget
constraints and the benefits that can be obtained by the replacement of the controllers. This thesis
presents the Methodology adopted for the Migration Plan and a case study implementation on the
Northern Virginia Region. Finally it presents the conclusions drawn from the research with
insights into the scope for further research.
iii
ACKNOWLEDGEMENTS
I would like to thank my advisor, Dr. Montasir M Abbas, for granting me the opportunity
to work on his research group. I am ever grateful for his guidance and support in my research.
His never-ending encouragement has helped me to successfully complete my Masters while at
Virginia Tech. He helped me in the most distressed part of my research when things did not seem
to be going right. His support and encouragement has increased my confidence and helped in
achieving things which I never thought of overcoming. My fear for programming is one such
example for that.
Additionally I would like to thank Dr. Kathleen Hancock, for her guidance and valuable
advice in the defense and in the field of GIS, and Dr. Gerardo Flintsch, for constructive
comments and advice in the defense.
I would like to thank Peter Sforza, Seth Peery, and Thomas Dickerson from the Center
for Geospatial Information Technology for helping me with the GIS programming and
applications. I would also like to thank my friends Yatish, Zain, Milos and Linsen for their
valuable guidance throughout the research process.
DEDICATIONS
I would like to dedicate this thesis to my parents for the love and affection which they
shared with me throughout my life. Without their encouragement and support I wouldn’t have
completed my studies. I also like to thank my friends Vamsi, Deepti and Shyam who have
always helped me and supported me both mentally and emotionally throughout my stay at
Blacksburg. I also thank all my friends who always encouraged me and made me laugh in the
hardest days of my work.
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TABLE OF CONTENTS
ABSTRACT ...……………………………………………………………………………………ii
ACKNOWLEDGEMENTS ...……………………………………………………………………iii
DEDICATIONS..........……………………………………………………….…………………..iii
TABLE OF CONTENTS ............................................................................................................... iv
LIST OF FIGURES ....................................................................................................................... vi
LIST OF TABLES ........................................................................................................................ vii
1. INTRODUCTION ...................................................................................................................... 1
1.1 LITERATURE REVIEW ......................................................................................................... 1
1.2 RESEARCH OBJECTIVES ..................................................................................................... 5
1.3 THESIS CONTRIBUTION ...................................................................................................... 5
1.4 THESIS ORGANIZATION...................................................................................................... 5
2. A MULTI-CRITERIA DECISION MAKING TECHNIQUE FOR SELECTION OF
TRAFFIC SIGNAL CONTROLLERS BASED ON CRITICAL FUNCTIONAL
REQUIREMENTS .......................................................................................................................... 7
ABSTRACT .................................................................................................................................... 8
2.1 INTRODUCTION .................................................................................................................... 9
2.2 MULTI-CRITERIA DECISION MAKING ............................................................................. 9
2.3 FUNCTIONAL REQUIREMENTS ......................................................................................... 9
2.4 EVALUATION PROCEDURE .............................................................................................. 10
2.4.1 Scoring Criteria ................................................................................................................ 10
2.4.2 Assignment of Weights .................................................................................................... 14
2.5 CALCULATION OF PERFORMANCE INDEX .................................................................. 15
2.6 CONCLUSIONS AND FUTURE WORK ............................................................................. 16
3. A GIS-BASED MULTI-OBJECTIVE OPTIMIZATION FRAMEWORK FOR
DETERMINATION OF NEW TRAFFIC SIGNAL CONTROLLERS MIGRATION PLAN ... 17
ABSTRACT .................................................................................................................................. 18
3.1 INTRODUCTION .................................................................................................................. 19
3.2 MIGRATION PLAN .............................................................................................................. 19
3.3 METHODOLOGY ................................................................................................................. 20
3.3.1 Zonal Classification.......................................................................................................... 20
3.3.1.1 Calculation of Performance Index ............................................................................. 20
3.3.1.2 Scoring Criteria.......................................................................................................... 21
3.3.1.3 Assignment of Weights ............................................................................................. 21
3.3.1.4 Calculation of Benefit Values .................................................................................... 21
3.3.2 System Replacement Decision ......................................................................................... 21
3.3.3 Optimization Process........................................................................................................ 22
3.3.3.1 Calculation of Degree of Detachment ....................................................................... 23
3.3.4 Output ............................................................................................................................... 23
3.4 CASE STUDY ........................................................................................................................ 23
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3.5 CONCLUSIONS AND FUTURE WORK ............................................................................. 26
4. APPLICATION OF THE MIGRATION PLAN ...................................................................... 27
4.1 CRITERIA FOR SELECTING THE FUNCTIONAL REQUIREMENTS ........................... 27
4.1.1 Transit Priority ................................................................................................................. 27
4.1.2 Coordination ..................................................................................................................... 28
4.1.3 Pedestrian & Bike............................................................................................................. 28
4.1.4 Transition Plans ................................................................................................................ 29
4.1.5 General Traffic Operation ................................................................................................ 29
4.1.5.1 Traffic Responsive: .................................................................................................... 29
4.1.5.2 Left Turners: .............................................................................................................. 29
4.1.5.3 Timing Plans: ............................................................................................................. 29
4.1.5.4 Queue Detection: ....................................................................................................... 29
4.2 GRAPHIC USER INTERFACE FOR THE GIS FRAMEWORK ......................................... 30
5. SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS ................... 31
5.1 SUMMARY ............................................................................................................................ 31
5.2 CONCLUSIONS AND RECOMMENDATIONS ................................................................. 33
REFERENCES ............................................................................................................................. 34
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LIST OF FIGURES
Figure 3- 1 DOD Vs Total Benefit values for various solutions and the cost .............................. 26
Figure 4- 1 GUI buttons developed in the GIS framework .......................................................... 30
vii
LIST OF TABLES
Table 2- 1 Scoring Criteria and the Scores for Functional Requirements under General Traffic
Operations ..................................................................................................................................... 11
Table 2- 2 Scoring Criteria and the Scores for Functional Requirements under Traffic
Coordination and Plan Selection ................................................................................................... 12
Table 2- 3 Scoring Criteria for Functional Requirements under Signal Preemption and Priority 13
Table 2- 4 Scoring Criteria for Functional Requirements under Pedestrians and Bikes .............. 14
Table 3- 1 Attributes used in GIS for calculation of Benefit value at each intersection .............. 24
Table 3- 2 Attributes showing the total benefit value for each alternate system .......................... 24
Table 3- 3 Adjacent zone id’s for each corresponding zone ......................................................... 24
Table 3- 4 Attributes consisting of Zones to be upgraded for each corresponding solution ........ 25
Table 3- 5 Total benefit values for each solution along with the degree of detachment for an
Example Problem .......................................................................................................................... 25
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1. INTRODUCTION Traffic Signal Controllers play a vital role in the operation of a signalized intersection.
Due to growing traffic needs, the functions of the existing systems often fail to reach the desired
performance level. Hence, in order to increase the operational efficiency of the intersection,
many new additional features are to be implemented. But the compatibility constraints between
the existing and new systems lead to system replacement decisions. Usually, system replacement
decisions are made by experienced engineers based on two factors: 1) their practical working
knowledge, and 2) the period of time the system has been deployed in the field. But for large
projects, engineering decisions based only on experience should be supplemented with more
effective ways of decision making.
The research presented in this thesis is based on the need for a proper decision-making
process of system replacement. To accomplish the above-mentioned task, a strategic migration
plan has to be developed. The plan should consider the spatial location of the systems that have
to be replaced and the benefit of candidate systems based on local conditions (e.g., traffic
volume, type of road, pedestrian and vehicle flows, preemption requirements, transit
requirements).
In order to develop an effective migration plan for the system replacement, it is most
important to know the existing system capability and its functional capacity. This thesis presents
a methodology for evaluation of signal controllers and for creation of a migration plan. In an
effort to develop an evaluation technique for signal controllers, various traffic signal controllers
were considered for the study in this research. Information about the features available in each of
these controllers was obtained from their respective manuals and vendors. The migration plan
was built on a Geographic Information System (GIS) framework that uses a Multi-Criteria
Decision Making (MCDM) technique. An external Multi-Objective Optimization tool was
introduced for obtaining the solutions. The thesis shows the integration of GIS, MCDM, and the
optimization tool for creating a migration plan for the traffic signal controllers. This method not
only justifies the system replacement judgments but also shows the improvement which can be
obtained by replacing the system. The proposed methodology has the flexibility of evaluating
systems that are based only on certain features that depend on the local conditions of the field.
The whole methodology was applied on a demo file for the Northern Virginia Region (NOVA)
and was successfully implemented and tested.
1.1 LITERATURE REVIEW Multi-Criteria Decision Making Problems are mostly used to solve the non-spatial
problems that integrate several criteria or attributes. The ranking or grading of the alternatives or
attributes is mainly contingent upon the decision makers [1]. The number of decision makers
may vary depending upon the project or case considered and its scope. The MCDM is classified
into two different categories: Multi Attribute Decision Making (MADM) and Multi Objective
Decision Making (MODM) [2]. Studies [3] suggest that in Multi Attribute Decision Making,
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attributes are the elements which comprise a certain value that can be quantifiable based on a set
of criteria. These attributes would help in selecting the alternatives based on the individual
scoring or priority of the attributes for each of the alternatives. On the other hand in case of Multi
Objective Decision Making [4], multiple objectives are evaluated to select the optimum
objective.
The MCDM is being used in many fields and applications of engineering and science.
Roy [5] has established a general framework of MCDM that suggests a well-defined set of
feasible alternatives. This is very important since the MCDM technique is not appropriate when
the alternatives have no relation to each other. Well-defined set of attributes are also important so
that each of the attributes can be evaluated easily and can be quantifiable. The applications of
MCDM are vast and it has a flexibility to use any method to solve any of the problems that
involve multiple criteria and alternatives.
The use of MCDM has largely been in the Natural Resource Management [6] because of
the diversity and disputative nature of the problems associated with it. With the use of MCDM,
these problems can be narrowed down to single or appropriate solutions. Since the natural
resource management issue deals with the involvement of public interest and also includes
multiple attributes, this technique is mostly adopted. Gamini [6] has classified the MCDM
methods into two categories. He classified Multi-Attribute Value Theory (MAVT) method as a
quantitative riskless category, and Multi Attribute Utility Theory (MAUT) and Elimination &
Choice Expressing Reality (ELECTRE) methods as quantitative risk category.
The benefits of the MCDM are not only the selection of the appropriate decision, but also
the evaluation of the results in a multi facet form. Studies [7] suggest that MCDM has helped the
decision makers in learning about the decisions of others and increased understanding about the
decisions made. The MCDM was also known for its effective evaluation and faster decision
making ability. It also showed that Multi-Criteria Group Decision Making (MCGDM) [8] had
greater over all benefits apart from the decision making alone.
There are many models of MCDM which are available and some of them are summarized
by Jayanath and Gamini [9]. They classified MCDM into MAVT, MAUT and Analytical
Hierarchy Process (AHP). The MAVT was again classified into different methods. First one is
the Simple multi-attribute rating technique (SMART), where the rating of the attributes is done
on a scale basis. Second method is Weighted Summation technique where the weighted
summation is used as a measure of evaluation. Again the selection of these methods is purely
contingent on the problem and the decision makers. The MAUT is another technique which is
used to solve the MCDM problems. The AHP [10] uses either pair wise comparison so as to rate
the alternatives. The rate or comparison is done based on certain set of criteria arranged in a
network form. In this project the SMART was used to rate the attributes, where rating of the
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attributes was given based on a scale of 1-10. Some of the studies suggest that Multi Attribute
Utility Function (MAUF) [11] can be used in case of single utility function and weighting
parameters being associated with the individual attributes. The Equation (1-1) [11] mentioned
below shows the calculation of the Utility function.
(1- 1)
The Ut(x) is the utility which is defined by various attributes.
Uti(xi) is the single utility function of the attribute i.
The MCDM has also been used in the Enterprise Resource Planning (ERP) [12] projects
where the principles of MCDM are being applied to the ERP so as to increase its awareness in
the industry. Unlike traditional method of considering attributes, the MCDM would be focusing
more on values in the ERP projects. The research also provided new empirically founded
evidence of implementation of MCDM to the field of EPR which was very first of its kind. This
shows that the implementation of the MCDM technique is not restricted to certain fields only.
As mentioned above the flexibility of MCDM allows it to be used in various fields, but
the non-availability/uncertainty of the information makes it difficult to evaluate the criteria. This
leads to subjective judgments which are based on the experience of the decision makers [13].
Literature [14] suggest that the weights assigned are mostly based on by considering all the
alternatives and not on the decision makers alone. Shipley [14] has suggested that the decision
maker would compare the values of the alternatives with the ideal value. He further emphasizes
that the more the alternatives considered are closer to the ideal value, the greater would be the
uncertainty involved.
The use of MCDM in the field of transportation has not been so new. For example, the
MCDM is used in many problems for planning purposes. Massam [15] attempted to classify the
planning problem into three different components, which are plans, criteria and interest groups.
While comparing his analysis with the traditional method, the plans can be compared to the
alternatives considered. The criteria would be the scoring or ranking criteria and the interest
groups would be the decision makers. So this can be accounted as Multi Group Decision making
Problem in general. The measurement scales which were defined for the scoring are the ratio,
interval, ordinal and nominal. Based on the attributes or decision groups, the appropriate scoring
method is adopted.
Although MCDM techniques are used in solving many spatial problems like vegetation,
forest etc., major disadvantage is that the MCDM techniques do not consider the spatial aspects
directly. Ferdinando et al [16] says that due to this drawback the principles of MCDM are
unsuitable for Geographic Information System (GIS) applications. So in order to make the
applications of GIS suitable for the MCDM they have considered a subset of MCDM and used
that for the GIS as an extension. Another example of similar analysis is use of GIS for
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conservation and landscape planning. The preferences on the criteria are usually expressed in the
form of weights assigned by the decision makers. And these weights are coupled with GIS using
programming techniques and tools which are directly in the maps. The methodology adopted in
these kinds of problems is usually AHP. Since the landscape is a spatial entity and it is easier to
identify the locations using GIS, the AHP acts as the ideal method for comparing and assigning
the weights based on the relative importance of the alternatives. Mui-How [17] has used a similar
technique for forest conservation planning. AHP technique was used in this case where the
problem was represented graphically and weights were assigned based on the level of hierarchy.
In this method pair wise comparison was done so as to know the relative importance of the
alternatives and assign them the weights according to their importance.
Recent developments in GIS and its wide spread usage have increased its potential
application in solving Transportation Related Problems. The major problems solved in
Transportation using GIS are concentrated in the areas of Transit services and Route choice
behavior. There have been several applications in the Transit services which include selection of
Bus Stops [18] or Transit Route planning [19, 20], which involves use of GIS tools in identifying
the areas of improvement for effective transit service based on the location of the residents and
other factors. In addition, GIS is also used for solving the Urban Traffic Data [21] related
problems which integrate real time traffic data with the GIS system which is used in visually
identifying the varying traffic patterns and helps in further decision making. The applications are
further extended to make decisions for supporting other Transportation realm problems such as
identifying the Pedestrian crash zones [22], which can be used for the planning purposes so as to
take measures to ensure the pedestrian safety. GIS is also used as a data management tool, which
helps in managing Dynamic data [23] that changes over time. In this project, GIS is used as a
tool so as to identify the areas which need system upgrading.
This thesis presents a methodology which integrates the concepts of MCDM and GIS for
evaluation of signal controllers and to develop a methodology for creation of migration plan for
the traffic signal controllers. Based on the literature review [24] it has been identified that there
are no proper guidelines for system replacement decision or migration plans. In addition to that
there are no standard procedures for evaluation of various signal infrastructures. So this research
focuses on the aspect of developing a comprehensive and flexible methodology for selection of
effective candidate controllers and optimal migration plan.
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1.2 RESEARCH OBJECTIVES The major objectives of this research are:
To develop a methodology to evaluate various traffic signal controllers based on the
critical set of functional requirements.
To introduce a methodology for developing an optimal migration plan for traffic signal
controllers based on critical set of functional requirements.
To make sure that the developed methodology is flexible and can be used to update
existing migration plans in the future and at different places.
1.3 THESIS CONTRIBUTION This thesis presents a research effort to develop a methodology and a framework to
determine optimal migration plans. The framework produces optimal solutions that suggest
which traffic signal controllers need to be replaced based on the functional requirements of the
intersections and the associated costs. The developed framework also shows the relative benefit
of replacing the existing system with new systems. This actually helps in assessing the benefit of
replacement and can be used in the decision making process so as to select which zones would
be most appropriate for upgrading. The Multi-Criteria Decision Making technique which was
presented in the thesis would also help in deciding which signal controller would be more
effective in solving the traffic problems for local conditions.
1.4 THESIS ORGANIZATION The thesis is organized into five chapters. Chapter 1 gives a brief introduction of the
project which includes the past work in MCDM and GIS. It also includes the main objective and
contribution of this research to the field of Signal Systems. Chapter 2 presents a Multi-Criteria
Decision Making (MCDM) method for selection of traffic signal controllers. It explains various
Multi-Criteria Decision making techniques and its applications in many fields. It also describes
about the various Functional Requirements and how each functional requirement is categorized
into several controller feature requirements. It presents a method for evaluation of various traffic
signal controllers using an equation. Criteria for scoring were also established based on the
information from the manuals of the controllers and by directly contacting the vendors. The
chapter also contains the actual scores for three different types of controllers which were used in
the study. It also shows the calculation of the Performance of the three controllers for given
requirements and the analysis of the results. Further conclusions and recommendations were also
presented explaining how Multi-Criteria Decision Making technique would be used in evaluating
the performance of various traffic signal systems infrastructure and how it can be applied in the
field of transportation.
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Chapter 3 presents the methodology for developing an optimal migration plan using
Geographic Information Systems (GIS) and Optimization tools. The chapter also presents a
methodology using GIS framework which is used in developing a migration plan for traffic
signal controllers. The GIS framework includes the procedure for creation of the zones for
system upgrade, then adopting the Multi-Criteria Decision Making technique for evaluating the
new and existing systems. An external Multi-Objective optimization tool is used to obtain the
solution based on the objective functions. Then the solution is integrated with the GIS
framework and the zones to be upgraded are represented on the map. Chapter 4 explains the
application process of the migration plan. It explains the application of various functional
requirements under different traffic conditions. It also explains the Graphic User Interface (GUI)
buttons which were developed for the execution of the process. Chapter 5 presents the summary
and the conclusions of this research. It also suggests how the MCDM technique is useful for
application in other fields of civil engineering. Finally the further recommendations are also
presented on how the present method can be improved and how it would be useful for the
researchers.
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2. A MULTI-CRITERIA DECISION MAKING TECHNIQUE FOR SELECTION OF
TRAFFIC SIGNAL CONTROLLERS BASED ON CRITICAL FUNCTIONAL
REQUIREMENTS
Surender Ganta
Graduate Student, Dept. of Civil and Environmental Engineering
Virginia Tech,
Blacksburg, VA 24061
Phone: 540-998-1911
Montasir M. Abbas, Ph.D., P.E.
Assistant Professor, Via Dept. of Civil and Environmental Engineering
Virginia Tech,
Blacksburg, VA 24061
Phone: 540-231-9002
FAX: 540-231-7532
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ABSTRACT
This paper presents a method based on Multi-Criteria Decision Making (MCDM) technique to
evaluate various Traffic Signal Controllers. The method to evaluate the controllers depends on
the critical set of functional requirements. These functional requirements constitute to the actual
features in the controllers and were developed through discussion with professionals in the field
of signal system operations. Criteria for scoring the controller features were developed from the
information obtained from the vendors and the controller manuals. An illustration of the
proposed framework for comparing three different controller types is also included. Finally,
alternate methods were also suggested for evaluation purpose leaving scope for further research.
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2.1 INTRODUCTION Traffic Signal Controllers are one of the most important components of the Signal
Infrastructure which play a crucial role in the operation of a signalized intersection. There are
many types of traffic signal controllers which are commonly available in the market. Many of the
modern controllers are equipped with advanced features which help in effective signal operation.
Hence, it is important to know which controllers perform well under various traffic conditions.
As such, there are no recommended set of guidelines or procedures to help us in evaluating
signal controllers and to provide a numerical value of their performance. In this paper, a Multi-
Criteria Decision Making Technique was used to evaluate different traffic signal controllers and
rank them based on their performance under various traffic conditions.
2.2 MULTI-CRITERIA DECISION MAKING Multi-Criteria Decision Making (MCDM) is a problem solving technique where
alternatives are evaluated depending on the individual scoring of the attributes of the alternative.
Although the MCDM techniques were never used for evaluating the signal controllers, literature
[25] suggest that similar analysis has been done previously to evaluate other signal infrastructure
using the functional requirements. But the alternatives used were evaluated on a broader scale
and do not consider the features of the controllers.
A traffic signal improvement program [26] was developed by Denver Regional Council
of Governments for the signal infrastructure improvement. They have taken into account the
unreliable system communication effects and role of key signal corridors for improvement. Most
of the improvement plan dealt with, replacement or up-grading of the communication aspects of
signal infrastructure and extending the system control. Improvement measures were taken for
specific operational features such as, transit signal priority and development of signal timing
plans. But, the improvement plan does not take into account the comprehensive effect of traffic
signal controllers and their features.
Another major drawback of past efforts is that, the objectives do not consider the features
or attributes associated with each of them. This actually influences the decision making and
wouldn’t be flexible enough for the user to evaluate alternatives based only on certain attributes.
So MCDM has been adopted for this study for evaluating the alternatives which consists of
individual attributes. This method for evaluation of the alternatives is based on the functional
requirements.
2.3 FUNCTIONAL REQUIREMENTS Functional Requirements constitute the advanced features required in Traffic Signal
Controllers and other aspects of the Signal System Operation and Maintenance. These were
developed through discussions made by many professional traffic engineers dealing with signal
system operation [27]. These functional requirements were classified into nine categories and
various controller features were assigned to each of these categories depending on their function
and operation.
10
The categories are specified below:
General Traffic Operation
Traffic Coordination and Plan selection
Signal Preemption
Pedestrians and Bikes
Controller Hardware and Software
Data Archiving Needs
Maintenance Requirements
Real-time Performance Measures
System Communications
In this paper, an example evaluation of various controllers is conducted based on the
requirements of General Traffic Operation, Traffic Coordination and Plan Selection, Signal
Preemption and Priority, and, Pedestrians and Bikes. These four categories directly affect the
performance of the intersection in terms of delay, stops etc., whereas the remaining categories do
not have any direct influence on the performance of the intersection. These categories are mostly
related to the Traffic Control Center and do not constitute to the functional requirements of the
intersection. For example, the Controller Hardware and Software category has the requirement
for better User Interface devices, but this has no direct impact on the operation of the
intersection. Similarly, Data archiving needs has requirement for better database in the
controllers. But they do not have any direct influence on the intersection performance. For that
reason, only the first four categories are considered for evaluation in this paper.
2.4 EVALUATION PROCEDURE The MCDM technique consists of functional requirements with the individual scoring
criteria for all the specified controllers. An equation was developed to calculate the Performance
Index (PI) of various controllers based on the individual scores and the weight assigned to each
of the categories based on the functional requirements of a corridor.
2.4.1 Scoring Criteria In Multi-Criteria Decision Making, each of the attributes is assigned a certain value or
score. Depending on these scores, alternatives are evaluated and the best alternative is selected.
The scoring of the attributes is usually done by a decision maker(s). After reviewing the manuals
of various controllers, and having a thorough idea about various controller features and the
functional requirements, the scoring criteria were developed for ranking each of these attributes
for all the controllers. The rating was given on a scale of 0-5, which indicates the performance of
the particular feature or an attribute considered. Each of the attributes or the features is compared
with the minimum requirements and a comparison was done among the alternatives. The vendors
of the controllers were also contacted, to evaluate the performance of the features which were not
clearly stated in the manuals. After evaluating the attributes in all the methods mentioned the
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final scores were given. These scores can be changed based on further modifications,
improvements, or changes done to the controller features. Criteria for scoring are listed below in the
Table 2- 1, Table 2- 2, Table 2- 3, and Table 2- 4 for the four functional requirement categories
and for the three different type of controllers.
Table 2- 1 Scoring Criteria and the Scores for Functional Requirements under General Traffic
Operations
Functional Requirements Type
1
Type
2
Type
3 Scoring Criteria
Need for phase re-servicing,
quad re-servicing, etc.,
during Free or Coordinated
operation as standard features
2 2 0
Rated 2 points if feature is available in
free and coordination. Rated1 point if
only in free mode, and rated 0 if
option is not present.
Need to maintain existing
counting capability utilizing
the Detector Reset Line
1 1 1 Rated 1 if the detectors are able to
count.
Conditional Service under
Free or Coordinated
Operation
2 1 2
Rated as 2 if conditional service is
available in both free and
coordination, else rated as 1 if only in
free mode and 0 if option is not
present.
Programmable feature: Max
Recall shouldn’t cause max
timer to immediately start
counting down if we desire
0 0 0 Rated 1 if Max recall can delay the
max timer to start counting.
Detector Switching
capabilities 1 1 1
Rated 1 if detector switching option is
available, else rated as 0.
Flexible detector Mapping 1 1 1 Rated 1 if possible else 0.
Queue Detection to override
normal timing by calling
preemption, alternate
coordination plan, or
different max setting
4 2 1
1. Only Queue detection:1 point, 2.
Initiate Preempt:1 point, 3. Alternate
Max Times:1 point, 4. Alternate
Pattern Mode:1 point.
16 Phase operation 1 1 0 Rated 1 if 16 phases, else 0.
Programming for LT Trap
concern - FYA
programming; Special
Protected/Permitted LT
programming
2 2 1
The controllers having Flashing
Yellow Arrow are ranked as 2 points
whereas controllers having feature to
prevent left turn traps but do not
provide FYA are rated 1 point.
Four (4) Timing Rings 1 1 0 Ranked as 1 if 4 timing rings, else
ranked as 0.
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Handling recurring situations
and localized peaks (e.g., for
schools)
0
1
Given 1 point if functions are
available for handling localized peaks.
If no special functions are available
then rated as 0.
Average Score (FR) 1.36 1.20 0.72
Table 2- 2 Scoring Criteria and the Scores for Functional Requirements under Traffic
Coordination and Plan Selection
Functional Requirements Type
1
Type
2
Type
3 Scoring Criteria
Offset per plan and transition
algorithms for achieving it. 3 3 1 Each offset is given 1 point
Look ahead ability to pick best
time to change coordination
plan to minimize transition
0 0 0 Rated 1 if it has ability to look
ahead to change coordination plan
More than 30 plans 1 1 0 Rated 1 is has more than 30 plans
Cycle Lengths exceeding 255
seconds 0 1 0 1 if more than 255 sec
Fixed versus floating force off
per phase per plan 2 2 0
1. Rated as 2 if Force-offs
available per phase and per plan 2.
If only per phase than rated as 1
point.
Holiday Date structured to
handle 40+ days 0 0 0 No Controller has 40+ holidays.
Holiday Events capable of
programming Time of Day
type function in addition to
events
1 1 1
If Holidays capable of
programming Time of day events
then rated as 1 point, else 0.
Ability to violate guaranteed
pedestrian programmed times
when developing coordination
plans
1 1 0
If the controller has the ability to
violate guaranteed pedestrian
programs then rated as 1 point.
Phase omit programming by
plan 1 1 1
If controller is capable of Phase
Omit per plan basis then rated as 1
point.
Method to confirm the current
Time of day/Day of week
setting in the controller
(Upload & Monitor controller
clock)
0 1 0
Rated 1 if the controller has the
capability to confirm the Time of
Day/Day of Week settings.
Traffic Responsive capable 0 1 0
Rated 1 point if the controller has
internal Traffic Responsive
capabilities.
13
Controller ability to execute
system-wide transition plan
directed from central control
center
0 0 1 Rated 1 point if capable of the
operation.
Average Score (FR) 0.75 1 0.33
Table 2- 3 Scoring Criteria for Functional Requirements under Signal Preemption and Priority
Functional Requirements Type
1
Type
2
Type
3 Scoring Criteria
Maximize emergency
response and related
features
4 3 3 Delay (1), Min Green (1), Min Walk (1),
Change Next Phase decision (1).
Have bus priority
(extended green only)
with more efficient ways
to recover from
preemption
2 1 2
1. Controllers having either TSP or soft
preempts for bus priority are rated as 1
point. 2. If recovery from low priority is
available then rated as 1 point.
Transit signal priority 2 1 2
(1) Controllers with Light Rail Vehicle
& Bus Priority are rated as 2. (2)Soft
preempt or bus priority are rated as 1
point. (3) And with no priority options
are rated as 0.
Communication
capabilities for adjacent
controllers (e.g., during
preemption)
1 0 0 If controllers are capable of Peer-to-Peer
Communication then rated as 1 point.
Phase selection for
exiting the Preemption 3 1 1
There are total 5 exit parameters 1. All
un-service phases receive service (1
point). 2. Place call on any specific Exit
Phase (1 Point). 3. Phases shortened will
get priority (1 point). 4. Phases waited
long will get priority (1 point). 5. Return
to Coordination directly. (1 point).
Entering into Normal Operation directly
is given 0 points.
Transition algorithms 0 1 0
If transition is available from
Preemption to Normal (not exit phases),
then rated as 1 point. If no transition
capabilities are mentioned then rated as
0 points.
Options for handling
"double" preemption 1 1 1
All controllers which can handle double
preemption are rated as 1 point.
14
Program and maintain
progression trough
preemption
0 1 0 Rated 1 if progression through
preemption is possible.
Average Score (FR) 1.625 1.125 1.125
Table 2- 4 Scoring Criteria for Functional Requirements under Pedestrians and Bikes
Functional Requirements Type
1
Type
2
Type
3 Scoring Criteria
Pedestrian Overlap capabilities -
operational under all
programming conditions such as
Free, Coordination, etc
2 2 2
1) Rated 2 if Overlap’s are
available in both free and
Coordination mode. 2) Rated 1 if
only under free operation.
Ability to assign more vehicle
phases with pedestrian phases 1 1 1
Rated 1 point if capable of the
operation.
Allow pedestrians to get 4
seconds advance green before
the phase
1 1 1 Rated 1 point if capable of the
operation.
Optional right arrow with
pedestrian phase 1 1 1
If right turn overlaps exist then
rated as 1 point.
Pedestrian phase re-service and
walk extension 1 0 1
Rated 1 if controller can take
extra pedestrian time from other
phases.
Different minimum pedestrian
time (push for normal, hold for
extend)
0 0 0
Rated 1 if controller has different
pedestrian times based on if the
button is pushed and if the button
is pushed and hold.
Vehicle clearance and
pedestrian clearance for
countdown purposes
1 1 1 Rated 1 point if pedestrian and
vehicle clearances are available.
Pedestrian clearance during
preemption 1 1 1
Rated 1 point if capable of
operation.
Average Score (FR) 1 0.875 1
2.4.2 Assignment of Weights The Critical set of functional requirements associated with an intersection should not
necessarily be given equal importance. In other words, a corridor might require both Transit and
Pedestrian facilities but the Transit features might be more important than the pedestrian
requirements. So the methodology has been framed in such a way, that it considers the
importance of each critical functional requirement at each intersection. To define the importance
and to quantify it a weight factor has been used, which requires assignment of a weight to each
of the critical functional requirement based on the intersection. This weight factor defines the
importance of each critical functional requirement for that intersection alone. The local
15
conditions must also be taken into account while assigning the weights. An example of a rational
approach to determine these weights for a given corridor would be, to determine the percentage
of intersections in a corridor (or a zone) where a given requirement (e.g., TSP) applies as will be
described below.
2.5 CALCULATION OF PERFORMANCE INDEX The actual methodology involves, evaluating the performance of various controllers at an
intersection according to its critical functional requirements and to suggest the most effective
controller for that intersection. So to evaluate the individual controllers a term called
Performance Index (PI) has been introduced. The PI of each of the controllers is calculated using
Equation (2-1) shown below.
(2- 1)
Where
PI - Performance Index of the controller
- Weight assigned to the critical functional requirement category ‘c’ on a scale of 1-10
FR= ∑ (Yi*Xi)/n
- 1 if the attribute (Functional Requirement) ‘i’ is considered, else 0
- The score of the attribute ‘i’ for the given controller.
n - Number of attributes considered in the given functional requirement category
The performance of a controller is evaluated using the above equation. From the tables
showing the scoring criteria and the scores, the FR values are calculated. Based on the FR values
obtained the performance of the controller is evaluated by assigning appropriate weights to
various Critical Functional Requirement Categories.
As an example consider a zone with certain number of traffic signal controllers. Each of
the intersection has to be evaluated to know the performance of the new system with the given
functional requirements. Considering the fact that General Traffic Operations and Signal
Coordination are most commonly needed at all intersections the weight of 10 is given to their
Functional Requirement categories. Now considering that the transit vehicle passes through 80%
of the intersections in this zone, weights of 8 is given to the preemption category. Assuming that
the pedestrian movements are present at 50% of the intersections, a weight of 5 is given to that
category. The FR values can be obtained from the previous tables for each of the controller type.
So the total performance can be calculated as shown below
PI for Controller Type 1:
So the PI for Controller Type 1 is PI = 1.185
PI for Controller Type 2:
16
So the PI for Controller Type 2 is PI = 1.071
PI for Controller Type 3:
So the PI for Controller Type 3 is PI = 0.744
The calculations above show that the Performance Index values for the three controllers
vary with same functional requirements and same weights. The results show that Controller Type
1 got a score of 1.185, Type 2 has obtained a score of 1.071 and Controller Type 3 which is the
existing type controller has got a score of 0.744. If the existing controller type 3 is replaced by
the new controller type 1 then the improvement with regard to FR satisfaction would be 59 %.
Whereas if the existing system is replaced by the controller type 2 than the performance would
be increased by 43%. From these calculations, it is evident that for the given functional
requirements and weights, controller type 1 is more effective than controller type 2 based on this
method. If Functional requirements for traffic coordination alone are considered then controller
type 2 should be more efficient since it has higher score than controller type 1. It can be observed
that the scores differ by the functional requirements considered and the weights assigned to each
of the categories of the functional requirements. So these weights can be assigned by the user
depending on the requirements and considering the field conditions.
By using the above mentioned formula, the PI values can be calculated for each of the
controller type. The PI values act as a scale in evaluating the controllers based on the features. It
acts as measure of the controller performance and represents the benefit of alternate systems in
terms of the score. Based on the requirements of the intersection each of the alternatives can be
evaluated using this procedure. The controller which gets higher score or benefit value can be
considered as more efficient based on this method.
2.6 CONCLUSIONS AND FUTURE WORK
This paper presents a method for evaluation of traffic signal controllers based on the
functional requirements using MCDM technique. An equation was developed which uses
functional requirements, scores and weights to calculate the performance of the controller.
Criteria were developed for scoring of the controller features depending on the information from
the manuals and from the vendors. Finally, this method was applied on three different controllers
and the benefit of replacing the controllers was also explained. This method serves as an
effective way for evaluating the signal controllers and to numerically represent its performance.
This method would further help the researchers by providing techniques for evaluation
of alternatives in case of large scale projects. This work can further be enhanced by developing a
method or an algorithm, that tests the system dynamics and assigns scores based on Measure of
Effectiveness expected from each controller features. The method developed can also be applied
for evaluation of other signal system infrastructure. The functional requirements specified in this
paper were developed based on the requirements of general signal system operations. These
functional requirements can be enhanced, or changed depending on the project.
17
3. A GIS-BASED MULTI-OBJECTIVE OPTIMIZATION FRAMEWORK FOR
DETERMINATION OF NEW TRAFFIC SIGNAL CONTROLLERS MIGRATION
PLAN
Surender Ganta
Graduate Student, Dept. of Civil and Environmental Engineering
Virginia Tech,
Blacksburg, VA 24061
Phone: 540-998-1911
Montasir M. Abbas, Ph.D., P.E.
Assistant Professor, Via Dept. of Civil and Environmental Engineering
Virginia Tech,
Blacksburg, VA 24061
Phone: 540-231-9002
FAX: 540-231-7532
18
ABSTRACT
Signal Replacement decisions are often made relying on the experience of the Traffic Engineers.
These decisions are made by considering the deployment time of the system, the new technology
available, and the performance of the system in the given location. But there are no set of proper
guidelines, or methods, which can quantify the system replacement decision for large scale
projects. In this paper we propose a methodology, for developing a migration plan for signal
controllers based on the functional requirements of the corridor. Geographic Information System
(GIS) is proposed as a tool to evaluate and identify the order of upgrade for different corridors
within the budget constraints. This paper addresses various aspects of optimizing the migration
plan, so that the users can evaluate the benefits associated with the system replacement. A Multi-
Criteria Decision Making technique was also used for estimating the benefits of replacing the
existing systems with various alternatives. Finally, the entire evaluation process and the
methodology for the migration plan were demonstrated on a GIS framework.
19
3.1 INTRODUCTION The objective of the project was to develop a Strategic Migration plan which indicates the
time frame and spatial location of the systems which has to be replaced, and what system is most
suitable depending on the functional requirements of the zone/corridor considered. In order to
develop the migration plan it is most important to know the existing system capability and its
functional capacity, and what type of systems are currently deployed in the field. The process
starts with classification of the region into various zones/corridors using Geographic Information
System (GIS). The second step is to evaluate the performance of the existing system and
evaluating the benefits of using alternate systems, with a Multi Criteria Decision Making
(MCDM) technique. And finally, to determine the zones to be upgraded using the optimization
technique.
3.2 MIGRATION PLAN This paper describes a method for creating a migration plan for traffic signal controllers.
But before making the system replacement decision, it is important to know under what
conditions or situations does the signal system has to be improved or upgraded. Literature [28]
suggests that the growth or change in traffic demand is one of the signs for signal improvements.
With increase in volume, the congestion becomes evident and this would be a clear indication for
the signal system improvement. Another measure indicating the need for signal improvement is,
frequent failures in the signal infrastructure equipment that results in inefficient operation of the
intersection. The need of advanced technology which is available in modern signal infrastructure
and not available in the existing infrastructure, can also serve as a measure for the need of system
upgrade. The study for the National Corporative Highway Research Program (NCHRP) [24]
indicates that, many of the system improvement plans are done using conventional techniques.
The process includes, reviewing the volume of the intersections or arterials, prioritization based
on volumes, identifying the needs and requirements, setting up goals and objectives, and
proceeding with the system upgrade. The alternative evaluation method is also done to evaluate
the benefits of the alternate system if the upgrade plan has to be carried. The study also suggests
that, some of the agencies also adopt the before and after technique’s, where simulation is done
to evaluate the benefits of system upgrade. Perhaps, this kind of procedure is very difficult in
case of macro level analysis.
The Traffic signal Policy and guidelines adopted by the Oregon Department of
Transportation [29] has provided some guidance for signal system installation and approval.
These guidelines mostly focus on the physical aspects of the road or intersection, the intersection
volume, existing level of service and existing and future traffic signal systems. But there are no
recommendations made as such for signal improvements/upgrade. Studies conducted by the
Columbus traffic signal system [25], provides a clear idea of the various aspects which are to be
considered while developing a migration plan. The study includes survey of various member
agencies, to know the existing traffic signal system infrastructure and the standards which are
adopted for the signal operation by those member agencies. It also suggests the evaluation of
20
various alternative traffic control systems and then developing a system implementation plan for
the communication and signal infrastructure.
All the above studies do not consider the functional requirements while developing the
system improvement plan. The base objective of this paper is, to develop a method to identify the
corridors or intersections which have to be upgraded based on the functional requirements. And
then, to develop a method to evaluate the benefits of implementation of alternate systems against
the existing signal infrastructure. The signal infrastructure term in this paper refers to the Traffic
Signal Controllers.
The system improvement plan can be broadly classified into two different tasks. First task
is to identify the existing system performance and relate it to the controller features. The second
task is to quantify and develop a method which suggests which systems are to be replaced first.
MCDM technique is adopted to evaluate the performance of signal controllers at each
intersection. Based on the functional requirements of the intersection, the performance of the
existing and new system is calculated. Then, the benefit of replacing the existing system with the
new system is estimated by calculating the difference between their performance values. Here
GIS is used to classify the whole area into zones based on the existing network. The benefit
values calculated from the MCDM technique is assigned to the respective zones in the GIS.
Following which an optimization technique is used, to find the zones to be upgraded first based
on the objective of maximizing the benefit values and minimizing the budget.
3.3 METHODOLOGY This section describes the actual methodology for the whole migration plan process. It includes
the integration of the GIS framework with the MCDM technique and optimization process.
3.3.1 Zonal Classification The zonal classification of the controllers is done based on the existing signal networks.
Each zone consists of a certain number of controllers which are operating together in a network.
Initially, each controller is assigned a unique value representing the zone in which it falls. So all
the controllers belonging to a particular zone has the same unique id. After that zones are created
using various tools available in Arc GIS [30]. The output would be the final zones showing the
controllers which fall in each zone. After creating the zone, now each controller has to be
evaluated to estimate its performance.
3.3.1.1 Calculation of Performance Index
All the controllers or intersections in each zone are evaluated against the functional
requirements. Each intersection has its own functional requirements, for which the performance
is calculated in terms of a score. These scores are obtained from the Multi-Criteria Decision
Making technique which is used for the evaluation of controllers. The performance of the
controllers is estimated from the scores assigned to the individual attributes of the alternatives.
These scores were assigned based on certain criteria.
21
3.3.1.2 Scoring Criteria
The criteria for scoring were developed keeping in view of the various features available
in different type of controllers. The features of the controllers were obtained from the manuals
and by contacting the vendors of various controllers studied. The scores were assigned on a scale
for each functional requirement for all the controllers.
3.3.1.3 Assignment of Weights
It is not necessary that each corridor has the same set of functional requirements. Some
corridors might have greater requirement for some categories of functional requirements than
others. So a weight factor was used to take into account the relative importance of one functional
requirement category over other. These weights are to be assigned carefully based on the
knowledge, experience and considering the local factors.
3.3.1.4 Calculation of Benefit Values
Each intersection is analyzed and weights are assigned depending on the importance of
the selected functional requirements at that intersection. Based on the functional requirements
considered at the intersection we get the corresponding score value of the intersection. This score
value is defined by the term called ‘Performance Index’ (PI), which is calculated for the existing
system as well as the alternative systems. Each of the alternatives is named as PI1, PI2, PI3, etc.
The scores for calculating the PI values are obtained from the MCDM Technique. The benefit
values are calculated at each intersection, which are represented as PI1_PI, PI2_PI, PI3_PI etc.
These benefit values are the difference in performance of the existing system and the new
alternate system. It can be represented as Benefit = (PIk-PI), where k is the alternate system
considered.
3.3.2 System Replacement Decision Conventionally, the system replacement decisions are generally made by the Traffic
Engineers based on their experience and considering the time since the system has been deployed
in the field. Evaluation of certain factors by conducting before and after studies is another
method of making the system replacement decision. But, there are no proper set of guidelines
that suggest the system replacement, considering field conditions and multiple factors for a larger
scale migration plan. This papers deal’s with the identification of these factors and attempts to
assess the performance of the existing system in those conditions. And check if the candidate
system can perform better in those conditions. If the new systems can improve the performance,
then the most effective alternative is selected based on the score of the systems. Usually the
system replacement is done for whole corridor or zone. Since the replacement of the system is
related to many other factors such as communication issues, operating in a network and
compatibility of the systems, the whole zone has to be replaced at once. Considering that, the
methodology has been framed in such a way that the whole zone is considered for replacement if
has to be upgraded to a new system.
After calculating the PI at each intersection, the PI values of all the intersections in a zone
are added together to get the total PI in that zone alone. Likewise for each zone the PI values are
22
obtained by the summation of the individual PI at each intersection. In addition to that, the
benefit of replacement of alternative systems is also calculated for the whole zone by summation
of benefit values at individual intersections. Now it has to be determined which zones are to be
upgraded first to get the maximum benefit value. This is done using an external optimization
technique.
3.3.3 Optimization Process The optimization process takes place outside the GIS program where the zones are
selected based on the objective function. There are many optimization techniques which are
adopted in general. But, the optimization problem itself has to be formulated mathematically
before solving it. There are many Mathematical programming formulations such as Linear
Programming, Multi-objective programming, Integer Programming, Multilevel Programming,
etc. The current problem can be formulated as a Linear Programming problem. The equations
can be modeled as shown below:
Objectives:
Maximize the Benefit value
(3- 1)
Minimize the Total budget
(3- 2)
Where
Bi = Benefit of Zone i which is calculated as PIi_PI
Zi = Design Variables which takes in the Binary value i.e., either 0 or 1
Ni = Number of controllers in Zone i
Ci = Cost of upgrading controller i
The above mentioned Equations represent’s the formulation for the given problem, which
can be solved using any optimization technique. The first objective function is, to select the
zones to maximize the total benefit values. The second objective function is, to minimize the
total cost which is incurred by upgrading the zones. The decision variable Zn is the output
indicating which zones are to be upgraded based on the objective function.
There are many optimization techniques used in general. Mukherjee [31] has classified
these optimization techniques into, Conventional optimization techniques and Non-Conventional
optimization technique. The Conventional technique includes the Iterative Mathematical search
technique to find the optimal solution. The problems were formulated as linear or non-linear
problems. On the other hand he classified the Non-Conventional techniques into various
techniques which included Heuristic search method, Genetic Algorithm (GA), Tabu Search (TS)
and Simulated Annealing (SA) technique.
From the above mentioned techniques, the GA optimization technique is the most
commonly adopted for many of the optimization problems. The GA [32] problems can again be
defined as Single Objective and Multi-Objective Problems. In the single objective problem only
23
one optimal solution set is obtained. Whereas, in Multi-Objective method many solutions are
obtained which are known as Pareto-optimal solutions. In the current problem, Multi-Objective
Optimization technique is used to get the multiple solutions.
3.3.3.1 Calculation of Degree of Detachment
Degree of Detachment (DOD) was introduced by Abbas et al [33] which is used as a
performance measure of scheduling continuity. It has been defined as, the degree by which a
zone is detached from its adjacent zones. In other words, the number of unselected adjacent
zones around a selected zone is the degree of detachment for that zone. So for each given
solution we get a DOD value. The lower DOD value indicates that the zones are more adjacent to
each other. The higher value indicates that the zones are more scattered in space. This DOD
value is important for the migration plan, since some of the organizations prefer upgrading the
zones based on the adjacency. In other words, randomly upgrading the zones is avoided to lower
the overall cost of upgrading. Hence it can be suggested that lower the DOD value, closer are the
zone’s that are to be upgraded.
3.3.4 Output
The output of the optimization tool consists of various zone combinations for the given
objective functions. Each corresponding solution consists of a set of zones which are to be
upgraded. So the total cost, total benefit and the DOD of upgrading those zones can be obtained.
A Pareto-front is drawn which indicates the total cost, total benefit and the DOD values for each
corresponding solution. The solutions above the surface of the Pareto-front are the sub optimal
solutions and the solutions below the surface are the infeasible solutions.
3.4 CASE STUDY The above methodology of the migration plan and MCDM was applied on a GIS
framework for the Northern Region of Virginia (NOVA). The Northern Regional Operations
(NRO) under Virginia Department of Transportation (VDOT) currently uses a 170 and NEMA
model traffic signal controllers. The number of traffic signal controllers which are currently
under operation in NOVA region is more than 1500. In this case, since the functional
requirements vary indefinitely, microscopic analysis of the signal controllers is a very tedious
task and not suitable for large scale migration plan. So a large scale analysis process has to be
adopted where controllers which come under same zone are replaced together.
The zonal classification of the controllers is done, based on the suggestions obtained from
VDOT. Each zone consists of a certain number of controllers, which are operating together in a
network. These zones are developed keeping in view the existing traffic signal controller
networks which operate together. The
Table 3- 1 below, show the attributes which are entered in GIS at each intersection. The
Unique Zone ID indicates the zone in which the intersection is operated, and the PI values
indicate the Performance Index values and benefit obtained by replacing the alternate systems.
24
Table 3- 1 Attributes used in GIS for calculation of Benefit value at each intersection
Signal Number Unique Zone ID PI PI1 PI2 PI1_PI PI2_PI
639130 8 4.3 7.9 7.9 3.6 3.6
627008 6 4 6.3 5.8 2.3 1.8
3215 7 4.1 6.2 5.3 2.1 1.3
3225 7 4.1 6.2 5.3 2.1 1.3
208035 4 3.6 6.2 5.1 2.6 1.5
3260 7 4.1 6.2 5.3 2.1 1.3
1440 2 3.5 6 5.4 2.5 1.9
After calculating the Performance Index values at each intersection, zones are created in
GIS using various tools. The ∑PI values and the benefit values are aggregated and assigned to
the whole zone. The Table 3- 2 below represents the attributes showing the total benefit value in
each zone.
Table 3- 2 Attributes showing the total benefit value for each alternate system
Unique Zone ID ∑PI ∑PI1 ∑PI2 ∑(PI1_PI) ∑(PI2_PI)
0 13.2 26.6 25.1 13.4 11.8
1 9.9 20.0 18.8 10.0 8.9
2 42.2 72.1 64.9 29.9 22.7
3 17.6 30.1 27.0 12.5 9.4
4 24.8 43.2 33.9 18.3 9.0
5 17.7 30.9 25.3 13.1 7.5
6 31.8 50.2 46.1 18.3 14.2
7 60.9 93.0 79.6 32.1 18.8
8 25.7 47.1 47.1 21.4 21.4
9 58.6 71.6 83.8 13.0 25.2
The DOD value for each solution is estimated by the DOD file. This file consists of
information about the adjacency of the zones. It gives the unique ID values of all the zones
which are adjacent to a given zone. Table 3- 3 below shows the zones which are adjacent to a
given zone. The first column indicates the zone which is considered and each row shows the
zones adjacent to that corresponding zone.
Table 3- 3 Adjacent zone id’s for each corresponding zone
Unique Zone ID 1 2 3 4 5
0 5 6 7 8 -
1 2 5 7 9 -
2 1 4 5 8 9
3 4 6 7 9 -
4 2 3 6 8 9
5 0 1 2 8 -
6 0 3 4 7 8
7 0 1 3 6 9
8 0 2 4 5 6
9 1 2 3 4 7
25
The table below shows the various solutions of the optimization process. Each solution
set represents the zones to be upgraded based on the objective function. The number represents
the corresponding controller type which is used in that zone. The value zero indicates that the
zone is not to be upgraded.
Table 3- 4 Attributes consisting of Zones to be upgraded for each corresponding solution
Unique Zone
ID Solution1 Solution2 Solution3 Solution4 Solution5 Solution6
0 1 2 0 4 0 0
1 1 2 0 0 0 6
2 0 2 0 4 5 6
3 0 2 0 4 0 0
4 0 0 0 4 5 6
5 0 0 0 0 0 6
6 0 0 3 0 0 0
7 0 0 0 0 0 0
8 1 0 3 0 0 0
9 1 0 3 0 5 0
After finding the zones to be upgraded for each corresponding solution, the total benefit
value, degree of detachment value and the total cost of upgrading those zones are estimated.
Here the cost of upgrading, relates only to the controller replacement cost and do not consider
external cost such as transportation cost, installation cost etc. The table below shows the total
benefit value, DOD and the total cost for each solution which is used to develop a Pareto-front.
Table 3- 5 Total benefit values for each solution along with the degree of detachment for an
Example Problem
Solution
Number
Total
Benefit DOD
Total
Cost ($)
1 70.5 26 140000
2 65.7 29 132000
3 52.7 27 150000
4 74.0 27 126000
5 61.1 18 195000
6 73.7 20 168000
The Figure 3- 1 below shows the various solutions with their total benefit values and the
corresponding DOD. Each solution is a combination of different zones which are to be upgraded.
It can be observed that lower the DOD value better is the migration plan, but at the same time the
total cost is on the higher side. Similarly when the cost is decreased the benefit value is also on
the lower side. So the optimal solution is selected to give the maximum benefit based on the
DOD and the total budget available.
26
Figure 3- 1 DOD Vs Total Benefit values for various solutions and the cost
3.5 CONCLUSIONS AND FUTURE WORK In this paper we presented a method for developing, optimal migration plan for traffic
signal controllers using GIS and Optimization techniques. We then show the utility of using GIS,
to classify the controllers into zones and to calculate the benefit associated with implementation
of the new system. The MCDM technique was suggested for evaluation of the controllers and to
calculate the system benefit values. The optimization technique was used, to specify which zones
are most appropriate for upgrade based on the objective function. Finally the zones are displayed
on the Map using GIS. This method is first of its kind where, GIS and optimization technique
both are used to develop a migration plan for traffic signal controllers. The method presented is
flexible enough so that it can be applied for any area for the signal system improvement. The
whole process was tested on a demo file which had the working GIS framework.
The methodology presented in this paper integrates GIS, MCDM and Optimization
technique to create a migration plan. This method can further be enhanced by improving the
optimization technique. The present method is limited by the cost function, which considers only
the cost of system replacement and do not consider external cost associated with it. The GIS
framework can further be improved, by providing better Graphic User Interface for easy
implementation of the whole process. This method can further be applied for developing
improvement plans for other signal system infrastructure as well, but not restricted to this alone.
27
4. APPLICATION OF THE MIGRATION PLAN
This chapter presents the application part of the migration plan which was explained
earlier. The migration plan developed is flexible enough to be applied elsewhere. But in order to
create a migration plan it is important to know about the functional requirements of a region and
functionality of the GIS framework. The first part of this chapter presents a set of guidelines
which helps in selecting the functional requirements under various traffic conditions. These
guidelines were developed after a thorough review of literature. These guidelines can be used
when this method is applied to a new region or area where the migration has to be implemented.
After selecting the functional requirements and calculating the performance index values
these are entered into the GIS database. Now the GIS database has to be integrated with the
optimization process for further analysis. The second part of this chapter describes the
functionality of the GIS framework and how it is integrated with the optimization tool. It also
explains about the Graphic User Interface (GUI) command buttons developed for the
implementation of the process.
4.1 CRITERIA FOR SELECTING THE FUNCTIONAL REQUIREMENTS The functional requirements were established based on the general requirements of the
signal system operation. Since the functional requirements at each intersection is not same, it is
important to know what functional requirements are to be selected under various traffic
conditions. The following is the certain set of guidelines that were developed after a thorough
review of literature. The guidelines suggest what type of functional requirements are to be
selected based on certain factors such as, location of the intersection, geometry of the
intersections, intersection type such as isolated or free etc. These guidelines can be used when
this migration plan has to be implemented in another location. These guidelines were classified
into various groups based on the functional requirements.
4.1.1 Transit Priority
Urban areas with larger population have a greater need for Transit Priority features to
reduce the overall delay and increase the serviceability. Research [34] shows that Transit Signal
Priority (TSP) provides benefits for the transit vehicles and has low system-wide impacts for low
traffic demands. So it can be recommended from the above studies, that implementation of TSP
on lightly congested approaches is not suggested when the conflicting approaches are heavily
congested. Further studies on arterials [35] show that signal preemption may not result in
oversaturated conditions, when sufficient green time is available in the system cycle length. It
also suggests that, the decision to grant transit priority at an intersection would actually result in
excess delay, if the arrival time of the transit vehicle is not taken into consideration.
From the above research the problems in Transit Priority can be accounted as follows:
Arterials with larger intersection spacing might require advance transit priority option or peer-to-
peer communication capabilities to avoid excess delays. Arterials with closer intersection
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spacing require systems to recover quickly from coordination immediately after preemption to
avoid saturated conditions. The frequency of transit vehicle and the number of approaches the
transit vehicle travel’s, specifies the need to handle dual preemption or number of preempt
sequences. For nearly saturated flows having greater transit priority requirements, the controllers
should be able to provide greater transition immediately after preemption.
Based on the problems associated with TSP, the following controller features can be
recommended: Traffic Signal Controllers having the peer-to-peer detection capabilities can be
used in case of arterials, to avoid excessive delays at the intersections. Controllers which allow
coordination in the background during preemption, helps in returning to direct coordination after
preemption. This feature is helpful in case of intersections with shorter spacing, to avoid the
queues created by disrupted system and avoid backing of vehicles to the upstream intersections.
4.1.2 Coordination Coordination of traffic signals is one of the major factors in arterials, to increase the
serviceability of the signal system and enhance smooth flow of traffic. Studies [36] show that
there are several factors which influence the selection of a control strategy which depend on
traffic, design and system characteristics. Literature review suggested that Fixed Time Signal
control in coordination is better suitable for intersections operating near to capacity, whereas
semi-actuated signal control is more effective for intersections with low volumes on actuated
phases. Fully actuated signal control as uncoordinated is more applicable for intersections which
are operating close to saturation on all approaches.
In order to deal with the problems of coordinate traffic signal systems, many modern
controllers are equipped with additional features. Some of them have the ability, to violate the
guaranteed pedestrian phases while developing the coordination plans. Some controllers offer
techniques which more likely act like a traffic responsive system in arterials. In addition to that
the techniques for platoon progression can be used for better coordination of the signals.
4.1.3 Pedestrian & Bike Most of the modern controllers offer many new features which can be implemented to
effectively manage the intersection vehicular and pedestrian flow. Literature [37] suggest that,
timing based on pedestrian minimum is more appropriate for longer cycle lengths and for
medium to high pedestrian crossing activities. In addition to that, pedestrian crossing with
protected left turn arrow [38] is also implemented to improve the efficiency of the signalized
intersection.
Some of the controllers have the ability to provide early green for pedestrians, which can
be incorporated based on the location and the pedestrian flow. Issues dealing with preemption
and pedestrian flows can be dealt with controllers providing minimum pedestrian clearance time
before preemption. In addition to that some of the 2070 controllers have special features for bike
signals which can be used in large cities with greater bike population.
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4.1.4 Transition Plans Selection of appropriate transition plan determines the operational efficiency of any
signalized intersection. Research [39] shows that one transition plan may not be appropriate for
all traffic conditions. Studies showed that, short transition is most effective in general but in
congested conditions add transition has performed better. There are many factors [40] which are
involved in the selection of transition schemes for exit preemption control. Such as vehicular and
pedestrian volume, signal timing plan, number of phases etc.
The modern traffic signal controllers have a greater ability in providing transition
schemes under various operations. Few 2070 controllers have the capability to make a smooth
transition from free to coordinated operation, which is required for nearly saturated intersections.
In addition to that some controllers have an ability to decide the transition method (Long-way,
Short-way/Long-way) to synchronize the offsets during coordination.
4.1.5 General Traffic Operation General traffic information is needed so as to categorize various operations available in
the controllers. Based on the data some of the features which might be required are:
4.1.5.1 Traffic Responsive: This feature is needed when there are unexpected traffic flows and
the timing plans are supposed to adjust to the traffic conditions. For saturated or nearly saturated
intersections this feature may not be an appropriate measure for selection. Traffic Responsive
Plan [41] selection would be more appropriate for abnormal traffic conditions and incidents or
events such as holidays. Many of the 2070 controllers are Traffic Responsive capable and can be
considered for replacing the 170 controllers.
4.1.5.2 Left Turners: Selection of left turn phasing schemes at signalized intersections depends
on the left turn and through traffic flows. Studies [42] showed that greater delays occurred in
case of protected phasing rather than protected permitted phasing. In addition to that National
Corporative Research Program (NCHRP) [43] has conducted evaluation of various traffic signal
displays for left turners. From the details provided by this report and from the safety point of
view of left turners it can be suggested that Flashing Yellow Arrow (FYA) signal head would be
more appropriate for heavy left turn lanes. The 2070 controllers are equipped with this feature
can be used in the field.
4.1.5.3 Timing Plans: For intersections with no greater change in flows throughout the day the
number of timing plans required might be less. Areas like CBD, recreational centers, schools and
shopping malls have varying traffic flow patterns and localized peaks. So in order to handle the
variations in the traffic flows the number of timing plans required is more. Many of the 2070
controllers offer many number of timing plans for various timings of the day.
4.1.5.4 Queue Detection: For corridors or arterials with smaller intersection spacing and higher
flows might require queue detectors so as to avoid blocking of the upstream intersections. 2070
controllers offer queue detectors and many additional features. These controllers have the ability
to alter the coordination plans or to initiate preemption when is detected. Many of the 170
Controllers do not offer such advanced features. So when implemented on an arterial or urban
corridor 2070 controllers would be a better option.
30
4.2 GRAPHIC USER INTERFACE FOR THE GIS FRAMEWORK The methodology presented in the thesis requires integration between GIS and the
optimization tool. The input for the optimization tool is obtained from the GIS database. This
database has to be converted into a different file format for the optimization tool to use it. So a
Graphic User Interface (GUI) was developed in Arc GIS using Arc Objects which acts as an
Application Programming Interface (API) for GIS.
Figure 4- 1 GUI buttons developed in the GIS framework
The Figure 4-1 shows the Graphic User Interface buttons which were developed in the
ArcGIS. The ‘Database to CSV’ button converts the GIS database into .csv file format. This file
acts an input to the Optimization technique. Another user interface button runs a batch file which
is used to execute the optimization tool. The output from the optimization tool is obtained in the
form of .csv file. This output is integrated to the GIS by using the ‘Join Output’ command
button. The ‘DOD’ [44] button is used to create the DOD file. These four GUI command buttons
help to easily create the migration plan.
31
5. SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS
5.1 SUMMARY The thesis presents a method to develop a migration plan for traffic signal controllers,
using Multi-Criteria Decision Making (MCDM) and Geographic Information System (GIS).
Increasing traffic demand has raised the need, for increased safety and efficiency of the
signalized intersections. But, the controllers which are already deployed in the field from long
time fail to achieve the desired performance in the intersection operation. This calls in the need
for system replacement decisions. Usually these decisions are made based on the knowledge and
experience of the traffic engineering professionals. But there are no proper guidelines, which can
evaluate the system replacement benefit, and suggest which systems are to be replaced first and
what systems are most effective under different conditions.
The project aims at developing a large scale migration plan considering the above
requirements. Due to the budget constrain and large number of controllers has to be replaced, the
migration plan has to be gradual rather than all at once. In addition, there are many traffic signal
controllers available in the market that performs equally well. Hence it is difficult to assess the
performance of these controllers based just on engineering judgment. So a procedure for an
optimal migration plan has been developed, which suggests which systems are to be replaced
first and what system suits best depending on the local traffic conditions. This procedure is based
on the MCDM and GIS.
This research provides an insight into various MCDM techniques which are commonly
adopted in many fields of engineering. It also gives a review of various decision making process
for signal system replacement. But these methods of decision making process are conventional in
nature and often lack the ability to demonstrate the reasons for system replacement. This thesis
provides a method for evaluating various signal controllers and to estimate their performance and
indicate them in the numerical forms. This often helps in providing proper substantial evidence
for system replacement judgments.
In order to evaluate various traffic signal controllers it is important to study the various
features available in each of the controllers. These controller features are often related to the
intersection requirements which can also be called as functional requirements. These functional
requirements constitute many advance features in the controllers, which were developed based
on the discussion with the professionals in the field of signal system operation. Each functional
requirement category consists of, the corresponding features or the requirements in the controller
for that category. For example, the Preemption and Priority category consists of, all the
functional requirements which are related to the Emergency Vehicle Preemption and Transit
Signal Priority features in the controller. Likewise for Pedestrians, Coordination, General Traffic
Operations, etc. These functional requirements were used for the evaluation of the signal
controllers based on decision making techniques.
A Multi-Criteria Decision Making (MCDM) technique was adopted in this project for
evaluation of the signal controllers. This technique has been considered in the project since it has
32
an advantage of considering multiple attributes for the evaluation process. The functional
requirements are considered as attributes in this study. The scoring of the attributes was done
depending on the criteria which were developed. This criterion was based on the information
obtained from the manuals of the various controllers. In the process of creating the scoring
criteria, various vendors were also contacted to obtain the information about the controllers
which was not clearly defined in the manuals. An equation was developed to calculate the
Performance Index of the controllers for the given Functional Requirements. Using the equation
which was presented the performance of the controllers can be estimated for a given set of
functional requirements. This performance index acts as a measure of the controller effectiveness
for those requirements. After calculating the performance of the controllers, it is important to
estimate the benefit of the replacement of the existing system with the new system. This is used
for creation of the migration plan and to know the potential system replacement zones.
The migration plan was developed using a Geographic Information System (GIS)
framework which integrates the MCDM technique which was described earlier. The GIS tool is
used to classify the controllers into various zones. Each of these zones consists of the controllers
which operate together in the form of a network. If a system replacement decision is taken then
all the controllers in a given zone are replaced at once. Here the MCDM technique is used to
evaluate various systems and to find the most effective system for a given functional
requirements. After which, the benefit of replacement of the system is calculated by the
difference in the Performance index values of the new and existing system. Then the total benefit
of replacement of the zone is estimated by summation of all the benefit values of the controllers
in that zone. Now each zone has a benefit value which indicates which type of the system is
more effective. But, it is important to know which zones are to be upgraded first to obtain the
maximum benefit.
To find the order of the zones for system replacement an external Multi Objective
Optimization technique was adopted. This optimization technique suggests which zones are to be
upgraded, and what system would be suitable for the zone based on the relative benefit values.
The Multi-Objective Optimization considers the relative benefit of the system replacement and
the total budget constraints. After knowing the zones to be replaced from the optimization
technique, the Degree of Detachment was calculated for various solutions. This Degree of
Detachment is a measure of adjacency for each zone with respect to other zones. It determines
how relatively close the zones to be upgraded are. This is important since the system upgrades
are usually done in the zones which are more adjacent rather than picking the random zones
which are far apart.
After finding the zones to be upgraded the total cost, benefit and Degree of detachment
values are estimated for each corresponding solution. And the output of optimization solution is
integrated back to GIS, to graphically represent which zones are selected under each solution. A
Pareto front was plotted representing the degree of detachment, the total cost and the total benefit
value. The solution which is most optimal is selected from this graph and represented in the GIS.
33
The migration plan presented in this thesis is flexible enough to be applied elsewhere. In
order to enhance the flexibility of the migration plan certain guidelines were established which
help in selection of the functional requirements under various traffic conditions. These guidelines
were developed considering the intersection type, geometry and the physical location of the
intersection. A thorough literature review of various signal system operations was conducted for
developing these guidelines. These guidelines are expected to help the users in carefully
evaluating the functional requirements during the selection process. In order to further extend the
flexibility of the method a Graphic User Interface (GUI) was developed in GIS using Arc
Objects. This GUI helps the users to easily perform the above motioned tasks without significant
knowledge of GIS.
5.2 CONCLUSIONS AND RECOMMENDATIONS This thesis has presented a methodology for developing an optimal migration plan, for
traffic signal controllers using the GIS and MCDM frame work. The use of MCDM has been
extensive in various fields, but its usage in the field of signal system infrastructure is very rare. A
method for evaluating various alternative systems based on some critical factors was presented.
This opens the door for further research by applying the techniques of this method for other
problems in the field of Signal System Operation. The scoring criteria presented in this thesis
were developed considered only the feature of the controllers. But, in reality these features in
each of the controllers might perform differently. So a method can be developed where the
scores are assigned not just based on the manuals, but by actually testing each of the features of
the controllers through simulation, or field testing, and assigning the scores based on the
obtained results. In addition to that, the functional requirements presented were developed based
on the general signal system operations. These functional requirements can further be enhanced,
or new requirements can be introduced based on the technical advancements.
The GIS framework presented in this thesis, has an advantage of being flexible enough to
be applied in any migration plan of existing signal controllers. The limitation of the framework is
that it does not consider the external cost of system replacement such as installation cost,
management cost or transportation cost of the old systems. So the methodology can further be
enhanced, by considering ways to incorporate the implicit cost of the system replacement. Apart
from that that, the GIS framework alone can further be improved so that it contains a better
Graphic User Interface. In addition, new methods can be found, so that the optimization process
takes place inside the GIS frame work itself.
34
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